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3d2smiles_pretrain

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  1. README.md +196 -0
  2. generation_config.json +7 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: microsoft/git-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: 3d2smiles_pretrain
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # 3d2smiles_pretrain
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+
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+ This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0246
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+ - Accuracy: 0.9767
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 64
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|
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+ | 0.6225 | 0.0224 | 100 | 0.5675 | 0.0465 |
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+ | 0.3462 | 0.0448 | 200 | 0.3916 | 0.0465 |
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+ | 0.2917 | 0.0672 | 300 | 0.3042 | 0.0814 |
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+ | 0.2865 | 0.0896 | 400 | 0.2253 | 0.1163 |
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+ | 0.2157 | 0.1120 | 500 | 0.1793 | 0.2209 |
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+ | 0.1933 | 0.1344 | 600 | 0.1493 | 0.2442 |
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+ | 0.1408 | 0.1568 | 700 | 0.1414 | 0.2791 |
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+ | 0.1277 | 0.1792 | 800 | 0.1093 | 0.4709 |
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+ | 0.1661 | 0.2016 | 900 | 0.1403 | 0.4012 |
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+ | 0.0949 | 0.2240 | 1000 | 0.1010 | 0.4477 |
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+ | 0.1025 | 0.2464 | 1100 | 0.0873 | 0.5407 |
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+ | 0.069 | 0.2688 | 1200 | 0.0771 | 0.5 |
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+ | 0.1072 | 0.2912 | 1300 | 0.0724 | 0.5465 |
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+ | 0.0766 | 0.3136 | 1400 | 0.0780 | 0.6221 |
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+ | 0.0933 | 0.3360 | 1500 | 0.0592 | 0.6453 |
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+ | 0.0676 | 0.3584 | 1600 | 0.0643 | 0.6628 |
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+ | 0.0812 | 0.3808 | 1700 | 0.0667 | 0.6453 |
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+ | 0.0572 | 0.4032 | 1800 | 0.0561 | 0.6919 |
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+ | 0.0459 | 0.4256 | 1900 | 0.0502 | 0.6221 |
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+ | 0.0642 | 0.4480 | 2000 | 0.0538 | 0.6163 |
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+ | 0.0597 | 0.4704 | 2100 | 0.0440 | 0.6919 |
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+ | 0.0575 | 0.4928 | 2200 | 0.0531 | 0.6919 |
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+ | 0.0341 | 0.5152 | 2300 | 0.0526 | 0.7326 |
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+ | 0.0353 | 0.5376 | 2400 | 0.0493 | 0.6919 |
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+ | 0.0569 | 0.5600 | 2500 | 0.0599 | 0.6977 |
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+ | 0.043 | 0.5824 | 2600 | 0.0387 | 0.7616 |
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+ | 0.0356 | 0.6048 | 2700 | 0.0353 | 0.75 |
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+ | 0.0299 | 0.6272 | 2800 | 0.0331 | 0.8023 |
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+ | 0.044 | 0.6496 | 2900 | 0.0497 | 0.7093 |
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+ | 0.0402 | 0.6720 | 3000 | 0.0329 | 0.8023 |
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+ | 0.0354 | 0.6944 | 3100 | 0.0277 | 0.7849 |
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+ | 0.0353 | 0.7168 | 3200 | 0.0416 | 0.7558 |
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+ | 0.0326 | 0.7392 | 3300 | 0.0502 | 0.7035 |
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+ | 0.0434 | 0.7616 | 3400 | 0.0343 | 0.8140 |
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+ | 0.0547 | 0.7840 | 3500 | 0.0303 | 0.8488 |
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+ | 0.0208 | 0.8064 | 3600 | 0.0283 | 0.8837 |
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+ | 0.0162 | 0.8288 | 3700 | 0.0327 | 0.8198 |
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+ | 0.0282 | 0.8512 | 3800 | 0.0200 | 0.8605 |
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+ | 0.0325 | 0.8736 | 3900 | 0.0182 | 0.8547 |
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+ | 0.0238 | 0.8960 | 4000 | 0.0329 | 0.8314 |
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+ | 0.0304 | 0.9184 | 4100 | 0.0330 | 0.7733 |
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+ | 0.0184 | 0.9408 | 4200 | 0.0279 | 0.8663 |
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+ | 0.0142 | 0.9632 | 4300 | 0.0172 | 0.8837 |
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+ | 0.0274 | 0.9856 | 4400 | 0.0297 | 0.8140 |
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+ | 0.0125 | 1.0078 | 4500 | 0.0315 | 0.8605 |
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+ | 0.0205 | 1.0302 | 4600 | 0.0224 | 0.8779 |
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+ | 0.0177 | 1.0526 | 4700 | 0.0307 | 0.8953 |
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+ | 0.0257 | 1.0750 | 4800 | 0.0346 | 0.8605 |
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+ | 0.0119 | 1.0974 | 4900 | 0.0229 | 0.8430 |
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+ | 0.023 | 1.1198 | 5000 | 0.0366 | 0.8256 |
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+ | 0.0262 | 1.1422 | 5100 | 0.0329 | 0.8198 |
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+ | 0.0173 | 1.1646 | 5200 | 0.0523 | 0.7907 |
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+ | 0.0144 | 1.1870 | 5300 | 0.0252 | 0.8837 |
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+ | 0.0137 | 1.2094 | 5400 | 0.0277 | 0.8837 |
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+ | 0.0205 | 1.2318 | 5500 | 0.0216 | 0.8895 |
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+ | 0.0102 | 1.2542 | 5600 | 0.0279 | 0.8605 |
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+ | 0.0079 | 1.2766 | 5700 | 0.0261 | 0.9244 |
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+ | 0.025 | 1.2990 | 5800 | 0.0312 | 0.8605 |
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+ | 0.0109 | 1.3214 | 5900 | 0.0267 | 0.8605 |
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+ | 0.0155 | 1.3438 | 6000 | 0.0305 | 0.8140 |
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+ | 0.0113 | 1.3662 | 6100 | 0.0225 | 0.8953 |
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+ | 0.0119 | 1.3886 | 6200 | 0.0265 | 0.9244 |
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+ | 0.0079 | 1.4110 | 6300 | 0.0194 | 0.9012 |
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+ | 0.0131 | 1.4334 | 6400 | 0.0173 | 0.8837 |
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+ | 0.0064 | 1.4558 | 6500 | 0.0245 | 0.8721 |
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+ | 0.015 | 1.4782 | 6600 | 0.0142 | 0.8895 |
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+ | 0.0141 | 1.5006 | 6700 | 0.0211 | 0.9651 |
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+ | 0.0136 | 1.5230 | 6800 | 0.0278 | 0.8895 |
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+ | 0.0197 | 1.5454 | 6900 | 0.0262 | 0.9012 |
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+ | 0.0248 | 1.5678 | 7000 | 0.0192 | 0.8605 |
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+ | 0.0076 | 1.5902 | 7100 | 0.0233 | 0.9186 |
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+ | 0.0056 | 1.6126 | 7200 | 0.0234 | 0.8953 |
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+ | 0.0097 | 1.6350 | 7300 | 0.0211 | 0.8430 |
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+ | 0.0075 | 1.6574 | 7400 | 0.0098 | 0.9360 |
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+ | 0.0103 | 1.6798 | 7500 | 0.0273 | 0.8721 |
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+ | 0.0123 | 1.7022 | 7600 | 0.0058 | 0.9709 |
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+ | 0.0088 | 1.7246 | 7700 | 0.0182 | 0.9070 |
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+ | 0.014 | 1.7470 | 7800 | 0.0334 | 0.8779 |
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+ | 0.0056 | 1.7694 | 7900 | 0.0223 | 0.8837 |
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+ | 0.0096 | 1.7918 | 8000 | 0.0193 | 0.8837 |
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+ | 0.0086 | 1.8142 | 8100 | 0.0285 | 0.9244 |
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+ | 0.0047 | 1.8366 | 8200 | 0.0155 | 0.9535 |
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+ | 0.0031 | 1.8590 | 8300 | 0.0254 | 0.9302 |
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+ | 0.0168 | 1.8814 | 8400 | 0.0132 | 0.9186 |
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+ | 0.0081 | 1.9038 | 8500 | 0.0210 | 0.9128 |
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+ | 0.0069 | 1.9262 | 8600 | 0.0142 | 0.8663 |
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+ | 0.0038 | 1.9486 | 8700 | 0.0082 | 0.9302 |
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+ | 0.0077 | 1.9710 | 8800 | 0.0133 | 0.9419 |
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+ | 0.0025 | 1.9934 | 8900 | 0.0174 | 0.9012 |
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+ | 0.0075 | 2.0157 | 9000 | 0.0201 | 0.9477 |
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+ | 0.0008 | 2.0381 | 9100 | 0.0199 | 0.9302 |
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+ | 0.0081 | 2.0605 | 9200 | 0.0255 | 0.9012 |
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+ | 0.003 | 2.0829 | 9300 | 0.0096 | 0.9535 |
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+ | 0.0027 | 2.1053 | 9400 | 0.0203 | 0.9128 |
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+ | 0.0028 | 2.1277 | 9500 | 0.0249 | 0.9244 |
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+ | 0.0023 | 2.1501 | 9600 | 0.0240 | 0.9128 |
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+ | 0.003 | 2.1725 | 9700 | 0.0305 | 0.9767 |
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+ | 0.0063 | 2.1949 | 9800 | 0.0305 | 0.9593 |
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+ | 0.0041 | 2.2173 | 9900 | 0.0225 | 0.9419 |
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+ | 0.0021 | 2.2397 | 10000 | 0.0193 | 0.9360 |
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+ | 0.0065 | 2.2621 | 10100 | 0.0171 | 0.8895 |
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+ | 0.0018 | 2.2845 | 10200 | 0.0170 | 0.9535 |
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+ | 0.011 | 2.3069 | 10300 | 0.0257 | 0.9360 |
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+ | 0.0047 | 2.3293 | 10400 | 0.0128 | 0.9651 |
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+ | 0.0028 | 2.3517 | 10500 | 0.0226 | 0.9360 |
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+ | 0.0034 | 2.3741 | 10600 | 0.0250 | 0.8488 |
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+ | 0.0032 | 2.3965 | 10700 | 0.0211 | 0.9535 |
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+ | 0.001 | 2.4189 | 10800 | 0.0233 | 0.9767 |
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+ | 0.0021 | 2.4413 | 10900 | 0.0201 | 0.9477 |
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+ | 0.0032 | 2.4637 | 11000 | 0.0205 | 0.9419 |
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+ | 0.002 | 2.4861 | 11100 | 0.0222 | 0.9767 |
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+ | 0.0029 | 2.5085 | 11200 | 0.0230 | 0.9651 |
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+ | 0.0024 | 2.5309 | 11300 | 0.0220 | 0.9767 |
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+ | 0.003 | 2.5533 | 11400 | 0.0224 | 0.9767 |
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+ | 0.0034 | 2.5757 | 11500 | 0.0222 | 0.9593 |
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+ | 0.0002 | 2.5981 | 11600 | 0.0202 | 0.9709 |
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+ | 0.0015 | 2.6205 | 11700 | 0.0188 | 0.9651 |
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+ | 0.0035 | 2.6428 | 11800 | 0.0218 | 0.9651 |
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+ | 0.0075 | 2.6652 | 11900 | 0.0268 | 0.9302 |
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+ | 0.0008 | 2.6876 | 12000 | 0.0219 | 0.9651 |
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+ | 0.0014 | 2.7100 | 12100 | 0.0247 | 0.9767 |
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+ | 0.0013 | 2.7324 | 12200 | 0.0234 | 0.9767 |
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+ | 0.0006 | 2.7548 | 12300 | 0.0254 | 0.9767 |
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+ | 0.0008 | 2.7772 | 12400 | 0.0247 | 0.9709 |
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+ | 0.0005 | 2.7996 | 12500 | 0.0252 | 0.9651 |
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+ | 0.0011 | 2.8220 | 12600 | 0.0222 | 0.9767 |
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+ | 0.0002 | 2.8444 | 12700 | 0.0248 | 0.9767 |
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+ | 0.0042 | 2.8668 | 12800 | 0.0251 | 0.9709 |
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+ | 0.0012 | 2.8892 | 12900 | 0.0235 | 0.9767 |
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+ | 0.0004 | 2.9116 | 13000 | 0.0254 | 0.9593 |
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+ | 0.0013 | 2.9340 | 13100 | 0.0257 | 0.9593 |
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+ | 0.0029 | 2.9564 | 13200 | 0.0264 | 0.9651 |
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+ | 0.0008 | 2.9788 | 13300 | 0.0246 | 0.9767 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 101,
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+ "eos_token_id": 102,
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+ "pad_token_id": 0,
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+ "transformers_version": "4.48.1"
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+ }